An RRT* Based Method for Dynamic Mission Balancing for Urban Air Mobility Under Uncertain Operational Conditions

Abstract

Urban air mobility provides an enabling technology towards on-demand and flexible operations for passenger and cargo transportation in metropolitan areas. Electric verticaltakeoff and landing (eVTOL) concept is a potential candidate for urban air mobility platform because of its lower carbon emissions, lower noise generations and potentially lower operational costs. However, such a transportation model is subject to numerous complicated environmental and urban design factors including buildings, dynamic obstacles and micro-weather patterns. In addition, communication, navigation and surveillance quality-ofservice and availability would be affected on the overall system performance and resilience. Some social factors such as privacy, noise and visual pollution should also be considered to provide a seamless integration of the urban air mobility applications into the daily life. This paper describes an integrated RRT* based approach for designing and executing flight trajectories for urban airspace subject to operating constraints, mission constraints, and environmental conditions. The generated path is energyefficient and enables aerial vehicle to perform mid-flight landing for battery changing or emergency situations. Moreover, this paper proposes another approach that allows on-the-fly path replanning under dynamic constraints such as geofences or microweather patterns. As such, the approach also provides a method toward contingency operations such as emergency landing on the fly.

Multiobjective Modular Strategic Planning Framework for Low-Altitude Missions Within the Urban Air Mobility Ecosystem

“…If it is not, the last feasible point of the segment connecting nΓ(wn) to wn (i.e., xc) is used as the central point to perform a random extraction from a gaussian distribution (lines [20][21]. The random point xr becomes the next candidate point to add to the tree (i.e., xw) if the segment going from nΓ(xr) to xr is collision free (lines [22][23][24]. If there is a suitable candidate to be added to the tree (line 26), xw is added to the tree and connected to xn which is either its nearest neighbor, i.e., nΓ(xw) or its preceding point in the tree if its path to xw is feasible (line 27).…”

“…Weather-based path definition has been tackled both in strategical and tactical phase in [20]. Here, wind module information has been used either to optimize the overall flight time [21], [22] or to minimize the energy consumption of the UAV [22]- [24].…”

Security and Safety Concerns in Air Taxis: A Systematic Literature Review

“…Drone Net [48] NASA vehicle [11,32,54,66,67] Volocopter eVTOL [17] STUART [40,46] HAMSTER [40,41] Container framework [68] Modular data modeling [45] Based airspace management system [8] Straw-man architecture [7] TOL modes of the main modern flying cars [10] SWIM [11] BRECCIA [12] Systolic FLS architecture [13] Framework for level of autonomy [15] Security architectures aimed at UAVs, such as Drone Net [48], STUART [40], and HAM-STER [41], use different types of approaches. HeAlthy, Mobility, and Security-based data communication archiTEctuRe (HAMSTER) is a data communication architecture designed for improving mobility, security, and safety of the overall system [41].…”

“…The most widespread architecture in the literature, not only in terms of references but also in terms of technical software and hardware evolutions, is NASA's vehicle [11,32,54,66,67]. NASA has contributed efforts in the development of air taxi aircraft designs.…”

Real-Time On-the-Fly Motion Planning for Urban Air Mobility via Updating Tree Data of Sampling-Based Algorithms Using Neural Network Inference

“…We aim to continuously guarantee the optimized attributes and connections (parent indices) of the nodes on the tree, as well as the feasibility and optimality of the flight path to the destination. Traditional graph-rewiring techniques based on RRT*, which involve significant forward and backward propagation, are too time-consuming for real-time updates [14]. Instead, we utilize RL policies or GAIL generators to guide the update of tree connections and node attributes.…”